// Copyright 2024 Google LLC
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.

#include <assert.h>
#include <pthreadpool.h>
#include <stddef.h>
#include <stdint.h>
#include <string.h>
#include <xnnpack.h>
#include <xnnpack/common.h>
#include <xnnpack/log.h>
#include <xnnpack/node-type.h>
#include <xnnpack/operator-type.h>
#include <xnnpack/operator.h>
#include <xnnpack/params.h>
#include <xnnpack/subgraph-validation.h>
#include <xnnpack/subgraph.h>

static enum xnn_status create_copy_operator(const struct xnn_node* node,
                                            const struct xnn_value* values,
                                            size_t num_values,
                                            struct xnn_operator_data* opdata,
                                            struct xnn_code_cache* code_cache,
                                            xnn_weights_cache_t weights_cache) {
  assert(node->num_inputs == 1);
  assert(node->num_outputs == 1);

  enum xnn_status status;
  switch (node->compute_type) {
    case xnn_compute_type_fp16:
      status =
          xnn_create_copy_nc_x16(node->flags, &opdata->operator_objects[0]);
      break;
    case xnn_compute_type_fp32:
      status =
          xnn_create_copy_nc_x32(node->flags, &opdata->operator_objects[0]);
      break;
    case xnn_compute_type_qs8:
    case xnn_compute_type_qu8:
      status = xnn_create_copy_nc_x8(node->flags, &opdata->operator_objects[0]);
      break;
    default:
      XNN_UNREACHABLE;
  }
  return status;
}

static enum xnn_status reshape_copy_operator(struct xnn_operator_data* opdata,
                                             struct xnn_value* values,
                                             size_t num_values,
                                             pthreadpool_t threadpool) {
  // Unpack the inputs.
  const uint32_t input_id = opdata->inputs[0];
  assert(input_id < num_values);

  // Call the underlying op.
  const size_t batch_size =
      xnn_shape_multiply_all_dims(&values[input_id].shape);
  enum xnn_status status = xnn_status_invalid_state;
  switch (opdata->operator_objects[0]->type) {
    case xnn_operator_type_copy_nc_x8:
      status = xnn_reshape_copy_nc_x8(opdata->operator_objects[0], batch_size,
                                      1 /* channels */, 1 /* input stride */,
                                      1 /* output stride */, threadpool);
      break;
    case xnn_operator_type_copy_nc_x16:
      status = xnn_reshape_copy_nc_x16(opdata->operator_objects[0], batch_size,
                                       1 /* channels */, 1 /* input stride */,
                                       1 /* output stride */, threadpool);
      break;
    case xnn_operator_type_copy_nc_x32:
      status = xnn_reshape_copy_nc_x32(opdata->operator_objects[0], batch_size,
                                       1 /* channels */, 1 /* input stride */,
                                       1 /* output stride */, threadpool);
      break;
    default:
      XNN_UNREACHABLE;
  }
  if (status != xnn_status_success) {
    return status;
  }

  // Get the sizes of the leading and trailing dimensions.
  const struct xnn_shape* input_shape = &values[input_id].shape;
  size_t leading_dims = 1;
  size_t trailing_dim = 1;
  if (input_shape->num_dims > 0) {
    for (int k = 0; k < input_shape->num_dims - 1; ++k) {
      leading_dims *= input_shape->dim[k];
    }
    trailing_dim = input_shape->dim[input_shape->num_dims - 1];
  }

  // Set the output size.
  const uint32_t output_id = opdata->outputs[0];
  assert(output_id < num_values);
  struct xnn_value* output_value = values + output_id;
  output_value->shape.dim[0] = leading_dims;
  output_value->shape.dim[1] = trailing_dim;
  const size_t new_size = xnn_tensor_get_size(output_value);
  if (new_size > output_value->size) {
    output_value->size = new_size;
    return xnn_status_reallocation_required;
  }

  return xnn_status_success;
}

static enum xnn_status setup_copy_operator(
    const struct xnn_operator_data* opdata, const struct xnn_value* values,
    size_t num_values, pthreadpool_t threadpool) {
  const uint32_t input_id = opdata->inputs[0];
  assert(input_id != XNN_INVALID_VALUE_ID);
  assert(input_id < num_values);

  const uint32_t output_id = opdata->outputs[0];
  assert(output_id != XNN_INVALID_VALUE_ID);
  assert(output_id < num_values);

  const struct xnn_value* input_value = values + input_id;
  const void* input_data = input_value->data;
  assert(input_data != NULL);

  const struct xnn_value* output_value = values + output_id;
  void* output_data = output_value->data;
  assert(output_data != NULL);

  switch (opdata->operator_objects[0]->type) {
    case xnn_operator_type_copy_nc_x8:
      return xnn_setup_copy_nc_x8(opdata->operator_objects[0], input_data,
                                  output_data);
      break;
    case xnn_operator_type_copy_nc_x16:
      return xnn_setup_copy_nc_x16(opdata->operator_objects[0], input_data,
                                   output_data);
      break;
    case xnn_operator_type_copy_nc_x32:
      return xnn_setup_copy_nc_x32(opdata->operator_objects[0], input_data,
                                   output_data);
      break;
    default:
      XNN_UNREACHABLE;
  }
}

enum xnn_status xnn_define_reshape_2d(xnn_subgraph_t subgraph,
                                      uint32_t input_id, uint32_t output_id,
                                      uint32_t flags) {
  enum xnn_status status;
  if ((status = xnn_subgraph_check_xnnpack_initialized(
           xnn_node_type_reshape_2d)) != xnn_status_success) {
    return status;
  }

  status = xnn_subgraph_check_input_node_id(xnn_node_type_reshape_2d, input_id,
                                            subgraph->num_values);
  if (status != xnn_status_success) {
    return status;
  }

  const struct xnn_value* input_value = &subgraph->values[input_id];
  status = xnn_subgraph_check_input_type_dense(xnn_node_type_reshape_2d,
                                               input_id, input_value);
  if (status != xnn_status_success) {
    return status;
  }

  switch (input_value->datatype) {
    case xnn_datatype_fp32:
    case xnn_datatype_qint8:
    case xnn_datatype_quint8:
      break;
    default:
      xnn_log_error("failed to define %s operator with input ID #%" PRIu32
                    ": unsupported Value datatype %s (%d)",
                    xnn_node_type_to_string(xnn_node_type_reshape_2d), input_id,
                    xnn_datatype_to_string(input_value->datatype),
                    input_value->datatype);
      return xnn_status_invalid_parameter;
  }

  status = xnn_subgraph_check_output_node_id(xnn_node_type_reshape_2d,
                                             output_id, subgraph->num_values);
  if (status != xnn_status_success) {
    return status;
  }

  const struct xnn_value* output_value = &subgraph->values[output_id];
  status = xnn_subgraph_check_output_type_dense(xnn_node_type_reshape_2d,
                                                output_id, output_value);
  if (status != xnn_status_success) {
    return status;
  }

  if (output_value->shape.num_dims != 2) {
    xnn_log_error(
        "failed to define %s operator with %zu-dimensional output shape: "
        "output must have exactly two dimensions",
        xnn_node_type_to_string(xnn_node_type_reshape_2d),
        output_value->shape.num_dims);
    return xnn_status_unsupported_parameter;
  }

  enum xnn_compute_type compute_type = xnn_compute_type_invalid;
  switch (output_value->datatype) {
    case xnn_datatype_fp32:
      compute_type = xnn_compute_type_fp32;
      break;
    case xnn_datatype_fp16:
      compute_type = xnn_compute_type_fp16;
      break;
    case xnn_datatype_qint8:
      compute_type = xnn_compute_type_qs8;
      break;
    case xnn_datatype_quint8:
      compute_type = xnn_compute_type_qu8;
      break;
    default:
      xnn_log_error("failed to define %s operator with output ID #%" PRIu32
                    ": unsupported Value datatype %s (%d)",
                    xnn_node_type_to_string(xnn_node_type_reshape_2d),
                    output_id, xnn_datatype_to_string(output_value->datatype),
                    output_value->datatype);
      return xnn_status_invalid_parameter;
  }

  status = xnn_subgraph_check_datatype_matches(
      xnn_node_type_reshape_2d, input_id, input_value, output_id, output_value);
  if (status != xnn_status_success) {
    return status;
  }

  status = xnn_subgraph_check_quantization_parameter_matches(
      xnn_node_type_reshape_2d, input_id, input_value, output_id, output_value);
  if (status != xnn_status_success) {
    return status;
  }

  struct xnn_node* node = xnn_subgraph_new_node(subgraph);
  if (node == NULL) {
    return xnn_status_out_of_memory;
  }

  node->type = xnn_node_type_reshape_2d;
  node->compute_type = compute_type;
  node->num_inputs = 1;
  node->inputs[0] = input_id;
  node->num_outputs = 1;
  node->outputs[0] = output_id;
  node->flags = flags;

  node->create = create_copy_operator;
  node->reshape = reshape_copy_operator;
  node->setup = setup_copy_operator;

  return xnn_status_success;
}
